哈普洛型大小对基因组选择精度和表观效应的影响:在大米中的实证研究
Maria Montiel1, Jose Moreno-Amores2, Jomar Punzalan3
1Horizon Ag LLC, Memphis, Tennessee, USA.
The plant genome
|November 28, 2025
概括
基因组选择的准确性随着较小的单元型大小而提高,这是由增加的重组驱动的. 在这项研究中,添加式+表观模型没有提高预测能力.
科学领域:
- 植物育种 植物育种
- 定量遗传学 是一个量子遗传学.
- 基因组学就是基因组学.
背景情况:
- 基因组选择 (GS) 整合了基因型和表型数据,以加速繁殖.
- 链接不平衡 (LD) 对GS至关重要,反映了历史的重组.
- 哈普洛型大小和LD模式受到重组率的影响.
研究的目的:
- 研究重组对哈普洛型大小和LD的影响.
- 评估GS预测能力 (PA) 的添加剂 (A) 与添加剂+表观 (A+I) 模型.
- 确定培训集 (TS) 单元型分辨率如何影响GS PA.
主要方法:
- 使用双亲 (MP2) 和多亲 (MP6-8) 种群,具有不同的重组率.
- 分析了LD衰变和再组合机会之间的相关性.
- 使用A和A+I遗传模型比较PA.
主要成果:
- 较高的重组导致较小的单 haplotype 块和更快的 LD 衰变.
- A+I模型增加了遗传性,但不是PA.
- 在TS中具有较小单元型大小的群体表现出增强的PA.
结论:
- 哈普洛型大小显著影响GS准确性.
- 增加的重组改进了哈普洛型分辨率,促进了GS PA.
- 结果引导育种者通过培训人口设计来优化GS策略.
相关概念视频
Epistasis Analysis
5.6K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
5.6K
Epistasis
50.0K
In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...
50.0K
Frequency-dependent Selection
23.0K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
23.0K
Genome-wide Association Studies-GWAS
15.2K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
15.2K
Trihybrid Crosses
25.2K
Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal...
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal...
25.2K
Chi-square Analysis
43.4K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
43.4K


